Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.
22,592 documents
This Supermind community post proposes selecting equities with RSI below 65, free-float market capitalization between 5 billion and 10 billion yuan, and a “main uptrend start” condition. It defines the latter through a price position within the recent…
This Chinese community post describes an equity screen requiring amplitude above 1, prior-day “main force control,” and a positive price-to-earnings ratio. It presents these as technical and fundamental filters intended to identify stocks with near-term…
This note presents a Chinese equity screen using four conditions: amplitude above 1, current volume above 10,000 lots, a higher open, and the 20-day moving average above the 120-day moving average. It interprets amplitude as a measure of price activity,…
This note describes a basic Chinese equity screen that selects stocks with daily amplitude above 1, prior-day turnover above 60 million, and price above its five-day moving average. It frames the filters as a combination of price activity, trading liquidity,…
This configuration specifies a Qlib workflow for training the HIST model on Alpha360 features for CSI 300 stocks and evaluating its signals in a portfolio backtest. The data handler normalizes features, fills missing feature values, drops rows without…
This post describes a stock screen pairing a minimum daily trading range with return on equity above a threshold for five consecutive years and at least one large one-day gain during a recent trading window. The intended combination seeks companies with…
This proposed A-share screen combines a market-cap ceiling, positive net profit, an RSI threshold, and positive afternoon large-order net inflows. The intended rationale is to pair a basic profitability constraint with a price indicator and a measure of…
This post proposes a Chinese stock screen using three filters: a turnover-ratio ranking among the top 100 stocks, a positive but capped return over the past ten days, and an opening price gain below a stated ceiling. The intended idea is to combine relative…
This April 2020 market note combines valuation, trading activity, sentiment, sector flows, and style factor monitoring to assess Chinese equities. It describes subdued market turnover and relatively low overall valuations, while agriculture-related stocks…
This Chinese equity screening idea combines RSI below 65, first-level bid volume greater than first-level ask volume, and a rounded price pattern described as an arc. The article interprets the RSI threshold as identifying a potentially oversold condition,…
This forum question concerns adding a moving-average exit condition to an AI stock-selection backtest. The proposed logic waits until a minimum holding period has passed, then examines positions in reverse StockRanker prediction order and sells eligible…
This note describes a Chinese equity screen combining three conditions: daily amplitude above 1, no limit-up close on the prior day, and an opening price near the 10-day moving average. It frames amplitude as a way to find more active stocks, excludes recent…
This stock-selection approach combines three filters: daily amplitude above 1%, a proxy for afternoon large-order net inflow, and a condition described as at least five moving averages aligning. The accompanying indicator expressions and Python example show…
This stock screen combines a capital-flow measure with valuation and trend filters. It favors Shenzhen main-board stocks with price-to-earnings ratios from 0 to 29.01 and price-to-book ratios from 0 to 3.11, then requires the 20-day moving average to be…
This post presents an equity screen requiring daily price amplitude above 1, a positive weekly MACD histogram, and exclusion of Beijing-listed shares. It describes amplitude as a way to filter out low-volatility stocks and the weekly histogram as a trend…
This post describes an equity selection screen that combines an RSI below 65 with seven consecutive declining sessions and excludes stocks that hit the daily price limit on the prior day. Its rationale is to identify recently weak stocks while avoiding those…
The document proposes screening Chinese A-share stocks using a daily amplitude threshold, a price condition around 18.5 yuan, and prior-day turnover between 3% and 28%. It explains these filters as ways to select stocks with notable price movement, a chosen…
The document describes a Better Volume indicator that classifies bars using volume, price range, candle direction, and estimated volume at the bid or ask. It colors a volume histogram for several conditions: high-volume wide-range up or down bars,…
This review of factor performance during the 2018–2020 quant crisis examines why diversified equity strategies struggled. It analyzes standard size, value, investment, profitability, and momentum factors, alongside portfolios formed by sorting stocks on size…
This report presents a three-layer fundamental quant framework: macro indicators and scenario analysis, sector-level earnings and valuation measures, and portfolio strategies. Its macro view combines growth, monetary and credit conditions, and inventory…
This post proposes screening equities for turnover within a specified range, seven consecutive down days, and a rising-bottom price pattern. It frames the combination as a way to examine stocks after a decline while looking for a possible base or rebound.…
This post describes a stock screen that combines at least five overlapping moving averages, a share price below a stated ceiling, and revenue growth between two fiscal years. The intended rationale is to find stocks with clustered trend measures and a…
This Chinese-language post proposes an equity screen using three conditions: amplitude above a threshold, rising price lows, and positive returns. The rationale is to exclude stocks with little movement, identify a potential base with progressively higher…
The document explains automated trading bots as programs that use market or other data to analyze conditions and place trades under a configured strategy. It describes potential benefits such as faster, more frequent execution and less emotion-driven…